Gal Elidan

Publication Activity (10 Years)

Years Active: 2000-2024
Publications (10 Years): 40

Top Topics

Markov Decision Process

Normal Distribution

Textual Entailment

Top Venues

IEEE Signal Process. Lett.

Publications

Avi Caciularu, Alon Jacovi, Eyal Ben-David, Sasha Goldshtein, Tal Schuster, Jonathan Herzig, Gal Elidan, Amir Globerson
TACT: Advancing Complex Aggregative Reasoning with Information Extraction Tools. CoRR (2024)
Irina Jurenka, Markus Kunesch, Kevin R. McKee, Daniel Gillick, Shaojian Zhu, Sara Wiltberger, Shubham Milind Phal, Katherine L. Hermann, Daniel Kasenberg, Avishkar Bhoopchand, Ankit Anand, Miruna Pîslar, Stephanie Chan, Lisa Wang, Jennifer She, Parsa Mahmoudieh, Aliya Rysbek, Wei-Jen Ko, Andrea Huber, Brett Wiltshire, Gal Elidan, Roni Rabin, Jasmin Rubinovitz, Amit Pitaru, Mac McAllister, Julia Wilkowski, David Choi, Roee Engelberg, Lidan Hackmon, Adva Levin, Rachel Griffin, Michael Sears, Filip Bar, Mia Mesar, Mana Jabbour, Arslan Chaudhry, James Cohan, Sridhar Thiagarajan, Nir Levine, Ben Brown, Dilan Görür, Svetlana Grant, Rachel Hashimshoni, Laura Weidinger, Jieru Hu, Dawn Chen, Kuba Dolecki, Canfer Akbulut, Maxwell L. Bileschi, Laura Culp, Wen-Xin Dong, Nahema Marchal, Kelsie Van Deman, Hema Bajaj Misra, Michael Duah, Moran Ambar, Avi Caciularu, Sandra Lefdal, Christopher Summerfield, James An, Pierre-Alexandre Kamienny, Abhinit Mohdi, Theofilos Strinopoulous, Annie Hale, Wayne Anderson, Luis C. Cobo, Niv Efron, Muktha Ananda, Shakir Mohamed, Maureen Heymans, Zoubin Ghahramani, Yossi Matias, Ben Gomes, Lila Ibrahim
Towards Responsible Development of Generative AI for Education: An Evaluation-Driven Approach. CoRR (2024)
Naama Rozen, Gal Elidan, Amir Globerson, Ella Daniel
Do LLMs have Consistent Values? CoRR (2024)
Roni Rabin, Alexandre Djerbetian, Roee Engelberg, Lidan Hackmon, Gal Elidan, Reut Tsarfaty, Amir Globerson
Covering Uncommon Ground: Gap-Focused Question Generation for Answer Assessment. ACL (2) (2023)
Paul Roit, Johan Ferret, Lior Shani, Roee Aharoni, Geoffrey Cideron, Robert Dadashi, Matthieu Geist, Sertan Girgin, Léonard Hussenot, Orgad Keller, Nikola Momchev, Sabela Ramos, Piotr Stanczyk, Nino Vieillard, Olivier Bachem, Gal Elidan, Avinatan Hassidim, Olivier Pietquin, Idan Szpektor
Factually Consistent Summarization via Reinforcement Learning with Textual Entailment Feedback. CoRR (2023)
Roni Rabin, Alexandre Djerbetian, Roee Engelberg, Lidan Hackmon, Gal Elidan, Reut Tsarfaty, Amir Globerson
Covering Uncommon Ground: Gap-Focused Question Generation for Answer Assessment. CoRR (2023)
Paul Roit, Johan Ferret, Lior Shani, Roee Aharoni, Geoffrey Cideron, Robert Dadashi, Matthieu Geist, Sertan Girgin, Léonard Hussenot, Orgad Keller, Nikola Momchev, Sabela Ramos Garea, Piotr Stanczyk, Nino Vieillard, Olivier Bachem, Gal Elidan, Avinatan Hassidim, Olivier Pietquin, Idan Szpektor
Factually Consistent Summarization via Reinforcement Learning with Textual Entailment Feedback. ACL (1) (2023)
Deborah Cohen, Moonkyung Ryu, Yinlam Chow, Orgad Keller, Ido Greenberg, Avinatan Hassidim, Michael Fink, Yossi Matias, Idan Szpektor, Craig Boutilier, Gal Elidan
Dynamic Planning in Open-Ended Dialogue using Reinforcement Learning. CoRR (2022)
Gal Yona, Shay Moran, Gal Elidan, Amir Globerson
Active learning with label comparisons. UAI (2022)
Gal Yona, Shay Moran, Gal Elidan, Amir Globerson
Active Learning with Label Comparisons. CoRR (2022)
Sella Nevo, Efrat Morin, Adi Gerzi Rosenthal, Asher Metzger, Chen Barshai, Dana Weitzner, Dafi Voloshin, Frederik Kratzert, Gal Elidan, Gideon Dror, Gregory Begelman, Grey Nearing, Guy Shalev, Hila Noga, Ira Shavitt, Liora Yuklea, Moriah Royz, Niv Giladi, Nofar Peled Levi, Ofir Reich, Oren Gilon, Ronnie Maor, Shahar Timnat, Tal Shechter, Vladimir Anisimov, Yotam Gigi, Yuval Levin, Zach Moshe, Zvika Ben-Haim, Avinatan Hassidim, Yossi Matias
Flood forecasting with machine learning models in an operational framework. CoRR (2021)
Yaron Shoham, Gal Elidan
Solving Sokoban with forward-backward reinforcement learning. CoRR (2021)
Oran Lang, Yossi Gandelsman, Michal Yarom, Yoav Wald, Gal Elidan, Avinatan Hassidim, William T. Freeman, Phillip Isola, Amir Globerson, Michal Irani, Inbar Mosseri
Explaining in Style: Training a GAN to explain a classifier in StyleSpace. CoRR (2021)
Yaron Shoham, Gal Elidan
Solving Sokoban with Forward-Backward Reinforcement Learning. SOCS (2021)
Yonatan Woodbridge, Gal Elidan, Ami Wiesel
Convex Nonparanormal Regression. IEEE Signal Process. Lett. 28 (2021)
Liran Katzir, Gal Elidan, Ran El-Yaniv
Net-DNF: Effective Deep Modeling of Tabular Data. ICLR (2021)
Oran Lang, Yossi Gandelsman, Michal Yarom, Yoav Wald, Gal Elidan, Avinatan Hassidim, William T. Freeman, Phillip Isola, Amir Globerson, Michal Irani, Inbar Mosseri
Explaining in Style: Training a GAN to explain a classifier in StyleSpace. ICCV (2021)
Zach Moshe, Asher Metzger, Gal Elidan, Frederik Kratzert, Sella Nevo, Ran El-Yaniv
HydroNets: Leveraging River Structure for Hydrologic Modeling. CoRR (2020)
Idan Szpektor, Deborah Cohen, Gal Elidan, Michael Fink, Avinatan Hassidim, Orgad Keller, Sayali Kulkarni, Eran Ofek, Sagie Pudinsky, Asaf Revach, Shimi Salant, Yossi Matias
Dynamic Composition for Conversational Domain Exploration. WWW (2020)
Yonatan Woodbridge, Gal Elidan, Ami Wiesel
Normalizing Flow Regression. CoRR (2020)
Ami Abutbul, Gal Elidan, Liran Katzir, Ran El-Yaniv
DNF-Net: A Neural Architecture for Tabular Data. CoRR (2020)
Sella Nevo, Gal Elidan, Avinatan Hassidim, Guy Shalev, Oren Gilon, Grey Nearing, Yossi Matias
ML-based Flood Forecasting: Advances in Scale, Accuracy and Reach. CoRR (2020)
Yotam Gigi, Sella Nevo, Gal Elidan, Avinatan Hassidim, Yossi Matias, Ami Wiesel
Spectral Algorithm for Shared Low-rank Matrix Regressions. SAM (2020)
Shai Rozenberg, Gal Elidan, Ran El-Yaniv
Improved Detection of Adversarial Attacks via Penetration Distortion Maximization. CoRR (2019)
Yotam Gigi, Ami Wiesel, Sella Nevo, Gal Elidan, Avinatan Hassidim, Yossi Matias
Spectral Algorithm for Low-rank Multitask Regression. CoRR (2019)
Sella Nevo, Vova Anisimov, Gal Elidan, Ran El-Yaniv, Pete Giencke, Yotam Gigi, Avinatan Hassidim, Zach Moshe, Mor Schlesinger, Guy Shalev, Ajai Tirumali, Ami Wiesel, Oleg Zlydenko, Yossi Matias
ML for Flood Forecasting at Scale. CoRR (2019)
Yoav Wald, Nofar Noy, Gal Elidan, Ami Wiesel
Globally Optimal Learning for Structured Elliptical Losses. NeurIPS (2019)
Nofar Noy, Yoav Wald, Gal Elidan, Ami Wiesel
Robust multitask Elliptical Regression (ROMER). CAMSAP (2019)
Deborah Cohen, Amit Daniely, Amir Globerson, Gal Elidan
Learning Rules-First Classifiers. AISTATS (2019)
Yonatan Woodbridge, Uri Okun, Gal Elidan, Ami Wiesel
Unmixing K-Gaussians With Application to Hyperspectral Imaging. IEEE Trans. Geosci. Remote. Sens. 57 (9) (2019)
Yotam Gigi, Gal Elidan, Avinatan Hassidim, Yossi Matias, Zach Moshe, Sella Nevo, Guy Shalev, Ami Wiesel
Towards Global Remote Discharge Estimation: Using the Few to Estimate The Many. CoRR (2019)
Deborah Cohen, Amit Daniely, Amir Globerson, Gal Elidan
Learning with Rules. CoRR (2018)
Yonatan Woodbridge, Gal Elidan, Ami Wiesel
Signal Detection in Complex Structured Para Normal Noise. IEEE Trans. Signal Process. 65 (9) (2017)
Martin Mladenov, Craig Boutilier, Dale Schuurmans, Ofer Meshi, Gal Elidan, Tyler Lu
Logistic Markov Decision Processes. IJCAI (2017)
Elad Eban, Mariano Schain, Alan Mackey, Ariel Gordon, Ryan Rifkin, Gal Elidan
Scalable Learning of Non-Decomposable Objectives. AISTATS (2017)
Yonatan Woodbridge, Gal Elidan, Ami Wiesel
Signal detection in para complex normal noise. ICASSP (2016)
Yonatan Woodbridge, Gal Elidan, Ami Wiesel
Quaternion structured paranormal distributions. ACSSC (2016)
Uri Heinemann, Roi Livni, Elad Eban, Gal Elidan, Amir Globerson
Improper Deep Kernels. AISTATS (2016)
Yaniv Tenzer, Gal Elidan
Generalized Ideal Parent (GIP): Discovering non-Gaussian Hidden Variables. AISTATS (2016)
Elad Eban, Mariano Schain, Ariel Gordon, Rif Saurous, Gal Elidan
Large-scale Learning With Global Non-Decomposable Objectives. CoRR (2016)
Yaniv Tenzer, Gal Elidan
HELM: Highly Efficient Learning of Mixed copula networks. UAI (2014)
Ofer Meshi, Elad Eban, Gal Elidan, Amir Globerson
Learning Max-Margin Tree Predictors. CoRR (2013)
Yaniv Tenzer, Gal Elidan
Speedy Model Selection (SMS) for Copula Models. CoRR (2013)
Yaniv Tenzer, Gal Elidan
Speedy Model Selection (SMS) for Copula Models. UAI (2013)
Gal Elidan, Nir Friedman
Learning the Dimensionality of Hidden Variables CoRR (2013)
Ofer Meshi, Elad Eban, Gal Elidan, Amir Globerson
Learning Max-Margin Tree Predictors. UAI (2013)
Elad Eban, Gideon Rothschild, Adi Mizrahi, Israel Nelken, Gal Elidan
Dynamic Copula Networks for Modeling Real-valued Time Series. AISTATS (2013)
Gal Elidan, Cobi Cario
Nonparanormal Belief Propagation (NPNBP). NIPS (2012)
Roi Reichart, Gal Elidan, Ari Rappoport
A Diverse Dirichlet Process Ensemble for Unsupervised Induction of Syntactic Categories. COLING (2012)
Gal Elidan
Inference-less Density Estimation using Copula Bayesian Networks CoRR (2012)
Gal Elidan, Ian McGraw, Daphne Koller
Residual Belief Propagation: Informed Scheduling for Asynchronous Message Passing. CoRR (2012)
Gal Elidan, Nir Friedman
The Information Bottleneck EM Algorithm CoRR (2012)
Gal Elidan, Benjamin Packer, Geremy Heitz, Daphne Koller
Convex Point Estimation using Undirected Bayesian Transfer Hierarchies CoRR (2012)
Gal Elidan
Copula Network Classifiers (CNCs). AISTATS (2012)
Gal Elidan
Lightning-speed Structure Learning of Nonlinear Continuous Networks. AISTATS (2012)
Iftach Nachman, Gal Elidan, Nir Friedman
"Ideal Parent" Structure Learning for Continuous Variable Networks CoRR (2012)
Gal Elidan
Bagged Structure Learning of Bayesian Network. AISTATS (2011)
Ariel Jaimovich, Ofer Meshi, Ian McGraw, Gal Elidan
FastInf: An Efficient Approximate Inference Library. J. Mach. Learn. Res. 11 (2010)
Gal Elidan
Inference-less Density Estimation using Copula Bayesian Networks. UAI (2010)
Gal Elidan
Copula Bayesian Networks. NIPS (2010)
Geremy Heitz, Gal Elidan, Benjamin Packer, Daphne Koller
Shape-Based Object Localization for Descriptive Classification. Int. J. Comput. Vis. 84 (1) (2009)
Stephen Gould, Jim Rodgers, David Cohen, Gal Elidan, Daphne Koller
Multi-Class Segmentation with Relative Location Prior. Int. J. Comput. Vis. 80 (3) (2008)
Geremy Heitz, Gal Elidan, Benjamin Packer, Daphne Koller
Shape-Based Object Localization for Descriptive Classification. NIPS (2008)
Gal Elidan, Stephen Gould
Learning Bounded Treewidth Bayesian Networks. NIPS (2008)
Gal Chechik, Geremy Heitz, Gal Elidan, Pieter Abbeel, Daphne Koller
Max-margin Classification of Data with Absent Features. J. Mach. Learn. Res. 9 (2008)
Gal Elidan, Benjamin Packer, Geremy Heitz, Daphne Koller
Convex Point Estimation using Undirected Bayesian Transfer Hierarchies. UAI (2008)
Gal Elidan, Iftach Nachman, Nir Friedman
"Ideal Parent" Structure Learning for Continuous Variable Bayesian Networks. J. Mach. Learn. Res. 8 (2007)
Gal Elidan, Ian McGraw, Daphne Koller
Residual Belief Propagation: Informed Scheduling for Asynchronous Message Passing. UAI (2006)
Gal Chechik, Geremy Heitz, Gal Elidan, Pieter Abbeel, Daphne Koller
Max-margin classification of incomplete data. NIPS (2006)
Ariel Jaimovich, Gal Elidan, Hanah Margalit, Nir Friedman
Towards an Integrated Protein-Protein Interaction Network: A Relational Markov Network Approach. J. Comput. Biol. 13 (2) (2006)
Gal Elidan, Geremy Heitz, Daphne Koller
Learning Object Shape: From Drawings to Images. CVPR (2) (2006)
John C. Duchi, Daniel Tarlow, Gal Elidan, Daphne Koller
Using Combinatorial Optimization within Max-Product Belief Propagation. NIPS (2006)
Gal Elidan, Nir Friedman
Learning Hidden Variable Networks: The Information Bottleneck Approach. J. Mach. Learn. Res. 6 (2005)
Ariel Jaimovich, Gal Elidan, Hanah Margalit, Nir Friedman
Towards an Integrated Protein-Protein Interaction Network. RECOMB (2005)
Yoseph Barash, Gal Elidan, Tommy Kaplan, Nir Friedman
Y. Barash, G. Elidan, T. Kaplan, , N. Friedman. Bioinform. 21 (5) (2005)
Iftach Nachman, Gal Elidan, Nir Friedman
"Ideal Parent" Structure Learning for Continuous Variable Networks. UAI (2004)
Gal Elidan, Nir Friedman
The Information Bottleneck EM Algorithm. UAI (2003)
Yoseph Barash, Gal Elidan, Nir Friedman, Tommy Kaplan
Modeling dependencies in protein-DNA binding sites. RECOMB (2003)
Gal Elidan, Matan Ninio, Nir Friedman, Dale Schuurmans
Data Perturbation for Escaping Local Maxima in Learning. AAAI/IAAI (2002)
Dana Pe'er, Aviv Regev, Gal Elidan, Nir Friedman
Inferring subnetworks from perturbed expression profiles. ISMB (Supplement of Bioinformatics) (2001)
Gal Elidan, Nir Friedman
Learning the Dimensionality of Hidden Variables. UAI (2001)
Gal Elidan, Noam Lotner, Nir Friedman, Daphne Koller
Discovering Hidden Variables: A Structure-Based Approach. NIPS (2000)